no code implementations • WMT (EMNLP) 2021 • Yongkeun Hwang, Hyeongu Yun, Kyomin Jung
Context-aware neural machine translation (NMT) incorporates contextual information of surrounding texts, that can improve the translation quality of document-level machine translation.
no code implementations • LREC 2022 • Hyeongu Yun, Yongil Kim, Kyomin Jung
Our method directly optimizes CKA to make an alignment between video and text embedding representations, hence it aids the cross-modality attention module to combine information over different modalities.
1 code implementation • 24 Feb 2024 • Soyoung Yoon, Eunbi Choi, Jiyeon Kim, Yireun Kim, Hyeongu Yun, Seung-won Hwang
We propose ListT5, a novel reranking approach based on Fusion-in-Decoder (FiD) that handles multiple candidate passages at both train and inference time.
no code implementations • 15 Mar 2023 • Yongil Kim, Yerin Hwang, Hyeongu Yun, Seunghyun Yoon, Trung Bui, Kyomin Jung
Vulnerability to lexical perturbation is a critical weakness of automatic evaluation metrics for image captioning.
2 code implementations • 28 Feb 2023 • Seonghyeon Ye, Hyeonbin Hwang, Sohee Yang, Hyeongu Yun, Yireun Kim, Minjoon Seo
In this paper, we present our finding that prepending a Task-Agnostic Prefix Prompt (TAPP) to the input improves the instruction-following ability of various Large Language Models (LLMs) during inference.
no code implementations • 13 Jan 2017 • Seunghyun Yoon, Hyeongu Yun, Yuna Kim, Gyu-tae Park, Kyomin Jung
In this paper, we propose an efficient transfer leaning methods for training a personalized language model using a recurrent neural network with long short-term memory architecture.